Vizbi – Build beautiful visualizations with and without code

We all know the fact that today’s world largely depends on technology. But how is technology built? Huge amount of coding, data and analytics go in the backend before a customer can see the final content and visual side.

The backend coding requires excellent technical skills to be able to update in the right way. Trust me, this education is not very easy and is not everybody’s cup of tea to expertise in coding and backend data management of technology.

Keeping this in mind, Shabda Raaj and Akshar Raaj came up with Vizbi – an analytics and visualization tool with built-in Python with machine learning support. This tool can revolutionize how analysts and data scientists work by providing all needed tools in one single platform.

Vizbi is Visualization + Business Intelligence. It can connect to numerous data sources which includes several relational data sources as well as Google BigQuery. This platform allows users to connect to PostgreSQL, MySQL, Amazon Aurora, MariaDB, Amazon Redshift, Bigquery and CSV files. Apart from the wide range that is already up for users, the team is also working on supporting more relational data sources as well as non-relational and document-oriented data source like Mongodb.

Vizbi allows users to create visualizations using drag and drop. Vizbi can infer the schema and relationship between tables of user’s data source and allows creating visualizations by dragging and dropping column names. In case drag and drop doesn’t suffice, the startup platform allows flexibility to switch to SQL mode.

Users can combine visualizations created from different data sources to build beautiful storyboards. You can see some of their favorite storyboards here. Storyboards could be in the form of chart visualizations or HTML. This enables users to tell a story with visualizations of their choice. That is why this feature is named ‘Storyboards’.

Vizbi provides a Python and R mode for running data analysis or doing data transformation. The analyzed and transformed data could be used to create visualizations.

Why Vizbi?

Vizbi is completely api driven unlike other existing BI tools in the market. So users have the ability to programmatically create and modify their visualizations and storyboards. A SaaS company might want to create different storyboards for different users of their system bases on user specific data. No problem, our apis can accommodate that too.

Vizbi has a 30 day trial period. And after the end of trial period user can decide to buy different plans based on the features they need.

“We provide Vizbi as a SaaS app in which case Vizbi will connect to your database. Or if you prefer to host it yourself and whitelable it, we have that covered too with our docker container based deployment models. Our on-premise install are also as simple as our cloud solutions, and can get a customer running within matter of hours.” Says the proud co – founder.

The team of StartupHyderabad got a chance to get in touch with the duo team and during that, we asked them the incident that led them to pioneer this amazing platform. This is what they had as an answer –

“We had to spend time cleaning and preparing data outside of our visualization tool and had to feed cleaned data in our tool.

On several occasions, they wanted to run numerical analysis on the data fetched from the database before rendering it as a visualization. But none of the existing tools allowed them to do so.

We didn’t find any existing tool which allows data preparation and data transformation along with ability to create beautiful visualizations. Either the tool allows visualization or it allows complex analysis but none of the existing tools allows both. So we started Vizbi to solve this problem.”

Talking about their plans for 2017, they are working on adding more data sources. They plan to support non-relational data sources like Redis and Mongodb. Right now Vizbi needs raw SQL for getting data from Bigquery. They are also trying to add drag and drop support for Bigquery.

They plan to provide more choices to machine learning professionals by adding support for tools like Tensorflow and Watson inside the platform.

Kudos team – this is an amazing platform and is surely going to solve lot of technical back end problems of technology users.

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